FRESHCODE’s Post

LeetCode Progress | 217. Contains Duplicate (Python) Today I solved “Contains Duplicate” on LeetCode. Problem: Given an integer array nums, return True if any value appears at least twice, otherwise return False. My approach: I used a dictionary to track numbers I’ve already seen. While iterating through the array: -- If the number is already in the dictionary, I return True -- Otherwise, I store it and continue What I learned: -- Using a dictionary makes duplicate detection efficient with average O(1) lookup time -- This gives an overall time complexity of O(n), which is optimal for this problem -- Choosing the right data structure can reduce complexity and make code cleaner #leetcode #python #dsa #datastructures #algorithms #coding #programming #problemSolving #softwareengineering #computerscience #interviewprep #codinginterview #100daysofcode #pythonprogramming

Recently, I explored how APIs work in Python, and understanding the full flow made things much clearer. From a client sending a request, to the backend handling validation, processing logic, interacting with data, and finally sending back a JSON response — everything fits together like a pipeline. Seeing the process visually helped me understand why APIs are so important in real-world applications like web platforms and ML systems. Still learning, still improving — but concepts like this make backend development feel less confusing and more exciting. #Python #API #BackendDevelopment #LearningInPublic #StudentDeveloper #TechJourney

Small Python tip that saves time (and makes code cleaner). A lot of people still manually split filenames to extract extensions. Which gets messy fast. But pathlib already gives you what you need: Cleaner, clearer, and built-in. Every time you replace manual string processing with a standard library tool, Your code becomes more readable and more robust.

Build AI agents in Python - the complete beginner's guide 🔄 Agent Loop - The core pattern 🔧 7 Built-in Tools - File ops, bash, web 🔌 MCP Native - Infinite extensibility 👥 Subagents - Task delegation ⚡ Hooks - Security & logging 🧠 Auto Memory - Context management Same SDK powering Claude Code. Now in your hands. Read the full guide: https://lnkd.in/dmibZSG3 #ClaudeCode #AI #Python #DevTools #AIAgents

# 𝑫𝒂𝒚 - 4 𝑷𝒚𝒕𝒉𝒐𝒏 𝑲𝒂 𝑫𝒂𝒊𝒍𝒚 𝑫𝒐𝒔𝒆 In Python 3.12 (the current stable standard), there are 35 reserved keywords. These are "reserved" because the Python interpreter uses them to recognize the structure of your code. Because of this, you cannot use these words as variable names, function names, or any other identifier. 𝐏𝐫𝐨-𝐓𝐢𝐩: 𝐒𝐨𝐟𝐭 𝐊𝐞𝐲𝐰𝐨𝐫𝐝𝐬 Python also has a few "soft keywords" like match, case, and _ (used in pattern matching). These act like keywords in specific contexts but can still be used as variable names elsewhere—though it's usually better to avoid doing that to keep your code clean! 😊 Run this in your terminal or IDE: 𝐢𝐦𝐩𝐨𝐫𝐭 𝐤𝐞𝐲𝐰𝐨𝐫𝐝 # To see the list of all keywords: 𝐩𝐫𝐢𝐧𝐭(𝐤𝐞𝐲𝐰𝐨𝐫𝐝.𝐤𝐰𝐥𝐢𝐬𝐭) # To see how many there are: 𝐩𝐫𝐢𝐧𝐭(𝐥𝐞𝐧(𝐤𝐞𝐲𝐰𝐨𝐫𝐝.𝐤𝐰𝐥𝐢𝐬𝐭)) #PythonProgramming #CodingTips #SoftwareDevelopment #PythonTips #CleanCode #ProgrammingLife #DataScience #BackendDeveloper

While running ML experiments or building configurable apps, if you’ve ever struggled with configurations scattered across YAML files, CLI arguments, environment variables, and code, OmegaConf is a Python library that solves this by providing a powerful approach to hierarchical configuration management. It brings everything together into one unified, type-safe, and composable configuration system, making experiments more reproducible and applications easier to reason about. With smart merging, lazy interpolation, resolvers, and structured configs, you can catch errors early and scale complexity without losing control. https://lnkd.in/g7ZaafSt #ConfigurationManagement #OmegaConf #Python #MachineLearning #MLOps

# 𝑫𝒂𝒚 - 5 𝑷𝒚𝒕𝒉𝒐𝒏 𝑲𝒂 𝑫𝒂𝒊𝒍𝒚 𝑫𝒐𝒔𝒆 👇 𝐒𝐭𝐨𝐩 𝐮𝐬𝐢𝐧𝐠 𝐚𝐬𝐲𝐧𝐜𝐢𝐨.𝐠𝐚𝐭𝐡𝐞𝐫() 𝐟𝐨𝐫 𝐜𝐨𝐦𝐩𝐥𝐞𝐱 𝐭𝐚𝐬𝐤𝐬. If you are still managing multiple concurrent tasks in Python using old patterns, you might be leaving your applications vulnerable to "zombie tasks" and silent failures. 𝐄𝐧𝐭𝐞𝐫 𝐒𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞𝐝 𝐂𝐨𝐧𝐜𝐮𝐫𝐫𝐞𝐧𝐜𝐲 𝐰𝐢𝐭𝐡 𝐚𝐬𝐲𝐧𝐜𝐢𝐨.𝐓𝐚𝐬𝐤𝐆𝐫𝐨𝐮𝐩. Introduced in Python 3.11, TaskGroup is the modern way to manage groups of tasks. Unlike asyncio.gather(), if one task in a group fails, TaskGroup ensures all other tasks in that group are cancelled automatically. 𝐖𝐡𝐲 𝐢𝐬 𝐭𝐡𝐢𝐬 𝐚 𝐠𝐚𝐦𝐞-𝐜𝐡𝐚𝐧𝐠𝐞𝐫? ✅ 𝐒𝐚𝐟𝐞𝐭𝐲: No more "leaked" tasks running in the background after an error. ✅ 𝐂𝐥𝐞𝐚𝐧 𝐄𝐱𝐜𝐞𝐩𝐭𝐢𝐨𝐧 𝐇𝐚𝐧𝐝𝐥𝐢𝐧𝐠: Uses ExceptionGroup to catch multiple errors at once. ✅ 𝐁𝐞𝐭𝐭𝐞𝐫 𝐅𝐥𝐨𝐰: The async with syntax makes it clear exactly where a group of tasks starts and ends. As we move through 2026, writing "Pythonic" code means writing robust code. Structured concurrency is no longer optional for senior devs—it's the standard. #Python #SoftwareEngineering #BackendDevelopment #AsyncIO #CleanCode #Python311 #ProgrammingTips #WebDev

How Python Manages Memory: Mutable vs Immutable One concept that silently affects performance, bugs, and behavior in Python is mutability. Immutable objects 👉 int, float, str, tuple Their value cannot be changed in place Any “modification” creates a new object in memory Safer, predictable, hashable (used as dict keys) Mutable objects 👉 list, dict, set Can be modified without changing memory reference Faster updates, but risk of unexpected side effects Changes reflect across all references Why this matters in real projects - Unexpected bugs when modifying lists passed to functions - Memory inefficiency when repeatedly modifying strings - Confusing behavior in function arguments & shared data #Python #MemoryManagement #Mutable #Immutable #PythonInternals #SoftwareEngineering

Doubling down on database ease! Did you know Dyne’s CRUDMixin brings Active Record style utilities to your SQLAlchemy models? ⚡️ It provides explicit, async helpers for common tasks like get, create, find, patch, and destroy, so you can stop writing repetitive query logic for simple operations. Clean code, powerful models: https://lnkd.in/eqEc4Tuw #Python #SQLAlchemy #Backend #DyneFramework #CleanCode

I built a VS Code extension to solve a problem I’ve personally faced for years: 𝗯𝗿𝗼𝗸𝗲𝗻 𝗣𝘆𝘁𝗵𝗼𝗻 𝗶𝗻𝗱𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻. Most existing formatters work well when code is already clean, but they often struggle when indentation is severely broken. That gap motivated me to build Python Indentation Healer — a tool focused specifically on restoring readable and executable Python code with a single action. 𝗛𝗼𝘄 𝗶𝘁 𝘄𝗼𝗿𝗸𝘀:   • Paste broken Python code using 𝗖𝗧𝗥𝗟 + 𝗩   • Press 𝗖𝗧𝗥𝗟 + 𝗔𝗟𝗧 + 𝗜 to automatically heal and re-indent the file I’ve already released 7 versions and continue improving it based on real-world usage and feedback. A short demo video is attached showing the transformation in action. 𝗚𝗶𝘁𝗛𝘂𝗯 𝗿𝗲𝗽𝗼𝘀𝗶𝘁𝗼𝗿𝘆: https://lnkd.in/dX7i-Qn4 𝗘𝘅𝘁𝗲𝗻𝘀𝗶𝗼𝗻 𝗹𝗶𝗻𝗸: https://lnkd.in/dusJq8UK Feedback, suggestions, and constructive criticism are very welcome. #𝗣𝘆𝘁𝗵𝗼𝗻 #𝗩𝗦𝗖𝗼𝗱𝗲 #𝗢𝗽𝗲𝗻𝗦𝗼𝘂𝗿𝗰𝗲 #𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿𝗧𝗼𝗼𝗹𝘀 #𝗣𝘆𝘁𝗵𝗼𝗻𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 #𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴 #𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 #𝗜𝗻𝗱𝗶𝗲𝗗𝗲𝘃 #𝗕𝘂𝗶𝗹𝗱𝗜𝗻𝗣𝘂𝗯𝗹𝗶𝗰